Intursion detection in Iot networks using feature selection and SVM classificastion
| dc.contributor.author | Hussein Al-Balhawi, Maryam Ali | |
| dc.contributor.author | Cansever, Galip | |
| dc.date.accessioned | 2022-08-08T13:24:52Z | |
| dc.date.available | 2022-08-08T13:24:52Z | |
| dc.date.issued | 2022 | en_US |
| dc.department | Enstitüler, Lisansüstü Eğitim Enstitüsü, Bilişim Teknolojileri Ana Bilim Dalı | en_US |
| dc.description.abstract | The steady growth in the number of devices connected to the Internet has attracted cyber criminals looking for vulnerabilities in computer networks and systems. The objective of this paper is to develop a model to identify DDoS, Infiltration, Web and Brute force attacks on computer networks, using Machine Learning (ML) techniques, increasing the accuracy, sensitivity, precision and measurement values. -F in relation to existing work. | en_US |
| dc.identifier.citation | Al-Balhawi, M. A. H., Cansever, G. (2022). Intursion detection in Iot networks using feature selection and SVM classificastion. In 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), IEEE. | en_US |
| dc.identifier.isbn | 9781665468350 | |
| dc.identifier.scopus | 2-s2.0-85133958959 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12939/2815 | |
| dc.indekslendigikaynak | Scopus | |
| dc.institutionauthor | Hussein Al-Balhawi, Maryam Ali | |
| dc.institutionauthor | Cansever, Galip | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings | |
| dc.relation.isversionof | 10.1109/HORA55278.2022.9799861 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Ulusal - İdari Personel ve Öğrenci | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | DDoS | en_US |
| dc.subject | IOT | en_US |
| dc.subject | Malware | en_US |
| dc.subject | ML | en_US |
| dc.title | Intursion detection in Iot networks using feature selection and SVM classificastion | |
| dc.type | Conference Object |
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